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Fronthaul data compression for Uplink CoMP in cloud radio access network (C-RAN)

机译:云无线电接入网络(C-RaN)中Uplink Comp的前传数据压缩

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摘要

The design of efficient wireless fronthaul connections for future heterogeneous networks incorporating emerging paradigms such as cloud radio access network has become a challenging task that requires the most effective utilisation of fronthaul network resources. In this paper, we propose to use distributed compression to reduce the fronthaul traffic in uplink Coordinated Multi-Point for cloud radio access network. Unlike the conventional approach where each coordinating point quantises and forwards its own observation to the processing centre, these observations are compressed before forwarding. At the processing centre, the decompression of the observations and the decoding of the user message are conducted in a successive manner. The essence of this approach is the optimisation of the distributed compression using an iterative algorithm to achieve maximal user rate with a given fronthaul rate. In other words, for a target user rate the generated fronthaul traffic is minimised. Moreover, joint decompression and decoding is studied and an iterative optimisation algorithm is devised accordingly. Finally, the analysis is extended to multi-user case and our results reveal that, in both dense and ultra-dense urban deployment scenarios, the usage of distributed compression can efficiently reduce the required fronthaul rate and a further reduction is obtained with joint operation.
机译:针对未来的异构网络(包括诸如云无线电接入网之类的新兴范例)的高效无线前传连接的设计已成为一项具有挑战性的任务,需要最有效地利用前传网络资源。在本文中,我们建议使用分布式压缩来减少云无线电接入网络的上行链路协作多点中的前传流量。与传统的方法不同,在传统方法中,每个协调点都将其量化并转发给处理中心,而这些观测在转发之前会被压缩。在处理中心,以连续的方式进行观测值的解压缩和用户消息的解码。这种方法的本质是使用迭代算法优化分布式压缩,以在给定的前传速率下实现最大用户速率。换句话说,对于目标用户速率,所产生的前传流量被最小化。此外,研究了联合解压缩和解码,并据此设计了迭代优化算法。最后,将分析扩展到多用户情况,我们的结果表明,在密集和超密集的城市部署场景中,使用分布式压缩可以有效降低所需的前传率,并且通过联合运营可以进一步降低。

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